Many wireless communications networks, such as public GSM (Global System for Mobile Communications) networks and private land mobile radio networks, use frequency modulation which has proven to be well suited to the mobile environment by reason of immunity to impulse noise which is common in such environments. However, these types of networks differ from those used for fixed microwave point-to-point communications services and satellite systems because the signals transported through these networks are subject to a greater degree of interference and distortion due to reflections and fading of the signals.
Signals arriving at or from a wireless communications device such as a mobile radio receiver or cellular telephone are almost always comprised of a complex amalgam of waves, some directly from the sending antenna and others reflected from stationary and moving objects. In the worst case scenario, the total received signal is composed of reflected signals. The resulting waveform caused by the combination of reflected signals (worse case) and/or direct signal plus reflected signals, is subject to cancellation or reinforcement in the amplitude domain as well as distortion in the time domain resulting from propagation delays over the varying length paths taken by reflected signals. Both the amplitude and time distortions make decoding of the signals more difficult. It is not uncommon for cancellation to reduce the incoming signal to a level far below the threshold required for reliable decoding by the receiver. This effect is referred to as multi-path fading.
In data systems, such cancellations or “drop outs” erase portions of the desired bit stream. The duration of the erasure is a function of the average signal strength, the wavelength of the radio signal, the speed of the vehicle (where the wireless device is being operated in a vehicle) and that of moving reflectors in the vicinity. Forward Error Correction (FEC) is a common technique for solving this erasure problem. Redundant information is added to the transmitted data to allow for a predicted level of erasures and recovery of the original data without re-transmission. FEC is useful but as the bit rate increases, more and more redundancy must be added which leads to diminishing returns. The redundancy reduces the effective bit rate of the system.
Another solution to problems caused by multi-path fading is to increase the complexity of the receiving system. Fading can be mitigated by receiving diversity signals such as by using multiple receivers. For a spatial diversity system multiple spaced-apart antennas are used and for an orthogonal diversity system a multiply polarized antenna is used. Other known diversity systems use frequency or time diversity. All such systems take advantage of diversity between two received signals, where each received signal carries the same transmitted information. A determination is made as to which signal is stronger and then the stronger signal is used, rather than the weaker one, to extract the information and thereby reduce the negative effects of fading. Most common are spatial diversity receivers comprising two or more receivers with separate antennas spaced an appropriate distance apart from each other so that the received signals are non-correlated give rise to probabilities that destructive interference experienced at one antenna may not be present on another.
Diversity receiving systems generally use one of three different classes of techniques to combine the multiple signals, being: (i) selection combining whereby the best signal is chosen based on assessment of signal strength (i.e. the signal having the best signal-to-noise ratio); (ii) equal gain combining whereby all signals are combined together regardless of the strength of any individual signal; and (iii) optimal combining whereby the signals are combined proportionally based on their individual strengths. Only the latter attempts to make use of the maximum possible information content available from all signals to yield optimal performance. However, in practice, it has been difficult to design combiner circuitry which effectively combines signals on such an optimal basis, the problem being to develop effective and practical algorithms for determining the weights to be applied. Many known optimal combiners use complex equalizers to implement an estimation of the received symbol sequences which is then used to proportionally weight the received signals for combining purposes. A further difficulty is posed by a need to develop means to align the diversity signals in such manner that they do not cancel (i.e. if one tries to directly add signals' orthogonal components, I1 to I2 and Q1 to Q2, this will result in cancellations akin to fading).
Accordingly, there is a need for an effective means of optimally combining signals in a diversity receiver which is less complex than those of the prior art and is able to avoid cancellations. Further, there is a need for such combining means which has a relatively low power consumption and may be implemented at relatively low cost.